People counting devices are typically used to count people entering and exiting doorways of stores. Typical doorways are entrances to stores in either open or enclosed malls. One type of people counting system is an overhead people counting system employing image sensors or thermal sensors to identify and count people entering or leaving a store. Information gathered by the sensors is analyzed and can be used by store managers to improve store sales performance and optimize scheduling of resources. The sensors have a limited field of view. In most cases, a single sensor may be used to “see” entrances with lengths of 6′ to 8′. Hence, in order to cover entrances wider than 8′ typical of mall-based stores, it is common practice to “cluster” two or more sensors to “see” much wider entrances; typically 24′ to 32′ in length. In other instances, multiple sensing devices can be interconnected to cover large entrances in excess of 32′ wide. In either configuration, the people counting system must count people entering and leaving doorways and report this information to a remote host computer through a dedicated communications interface, such as an Ethernet connection.
In a multi-device network, each of these devices is linked to another so as a system they appear to cover or “see” one contiguous wide exit. Typically, one of these devices is a “master” device, sensor or node and is in communication with other “slave” devices, sensors or nodes, where each slave node must “bind” to their master. Any overlap in the “field of view” must be communicated to and resolved by the master.
The master and slave devices must typically be configured to suit their environment. Such configuration includes but may not be limited to: setting up one or more virtual count lines, device IDs, physical and logical locations and their corresponding mapping, and various other set up parameters. Virtual count lines are virtual thresholds in memory used to delineate cross-over thresholds crossing the field of view, e.g., across a store entrance. Typically these parameters are downloaded on-site via a PC and stored within the hardware of the people counting system. In currently deployed systems, if a device fails and must be replaced, one has to install a new device and have it set up and re-configured all over again. This requires a field technician to visit the site, re-initialize the sensor, and download the set-up parameters all over again.
Devices currently installed in the field and more specifically sensors using Ethernet (Internet) connectivity, employ an Internet Protocol (“IP”) address that uniquely identifies the device from all other devices on the network. These address blocks are typically purchased, allocated and deployed by service providers to customers for devices that connect to the network. Given the widespread use of devices deployed across the Ethernet, institutions are reluctant to issue their IP addresses to manufacturers of Ethernet-based devices or use their assigned public IP addresses to support in-store security systems. In addition, when one of the devices fails for any reason, the device has to be replaced, requiring its IP address and configuration parameters to be manually downloaded again.
Therefore, what is needed is an efficient and cost effective system and method for automatically configuring devices in a security system, e.g., automatically configuring sensors in a people counting system.